An increasing number of tasks require people to explore, navigate and search extremely complex data sets visualized as graphs. Examples include electrical and telecommunication networks, web structures, and airline routes. The problem is that graphs of these real world data sets have many interconnected nodes, ultimately leading to edge congestion: the density of edges is so great that they obscure nodes, individual edges, and even the visual information beneath the graph. To address this problem we developed an interactive technique called EdgeLens. An EdgeLens interactively curves graph edges away from a person's focus of attention without changing the node positions. This opens up sufficient space to disambiguate node and edge relationships and to see underlying information while still preserving node layout. Initially two methods of creating this interaction were developed and compared in a user study. The results of this study were used in the selection of a basic approach and the subsequent development of the EdgeLens. We then improved the EdgeLens through use of transparency and colour and by allowing multiple lenses to appear on the graph.
IntroductionThe focused assessment with sonography for trauma (FAST) is a commonly used and life-saving tool in the initial assessment of trauma patients. The recommended emergency medicine (EM) curriculum includes ultrasound and studies show the additional utility of ultrasound training for medical students. EM clerkships vary and often do not contain formal ultrasound instruction. Time constraints for facilitating lectures and hands-on learning of ultrasound are challenging. Limitations on didactics call for development and inclusion of novel educational strategies, such as simulation. The objective of this study was to compare the test, survey, and performance of ultrasound between medical students trained on an ultrasound simulator versus those trained via traditional, hands-on patient format.MethodsThis was a prospective, blinded, controlled educational study focused on EM clerkship medical students. After all received a standardized lecture with pictorial demonstration of image acquisition, students were randomized into two groups: control group receiving traditional training method via practice on a human model and intervention group training via practice on an ultrasound simulator. Participants were tested and surveyed on indications and interpretation of FAST and training and confidence with image interpretation and acquisition before and after this educational activity. Evaluation of FAST skills was performed on a human model to emulate patient care and practical skills were scored via objective structured clinical examination (OSCE) with critical action checklist.ResultsThere was no significant difference between control group (N=54) and intervention group (N=39) on pretest scores, prior ultrasound training/education, or ultrasound comfort level in general or on FAST. All students (N=93) showed significant improvement from pre- to post-test scores and significant improvement in comfort level using ultrasound in general and on FAST (p<0.001). There was no significant difference between groups on OSCE scores of FAST on a live model. Overall, no differences were demonstrated between groups trained on human models versus simulator.DiscussionThere was no difference between groups in knowledge based ultrasound test scores, survey of comfort levels with ultrasound, and students’ abilities to perform and interpret FAST on human models.ConclusionThese findings suggest that an ultrasound simulator is a suitable alternative method for ultrasound education. Additional uses of ultrasound simulation should be explored in the future.
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